Litgu.ru - Литературный Гуру

Название: Logic in Computer Science
Автор: Hantao Zhang, Jian Zhang
Издательство: Springer
Год: 2025
Страниц: 488
Язык: английский
Формат: pdf (true), epub
Размер: 28.8 MB

Mathematical logic is an important basis for mathematics, Computer Science and Artificial Intelligence (AI) alike. This book provides a comprehensive introduction to various logics, including classical propositional logic and first-order predicate logic, as well as equational logic, temporal logic, and Hoare logic. In addition, it presents proof procedures for classical logics and decision procedures for checking the satisfiability of logical formulas. The book assumes no background in logic. It presents logics as practical tools for solving various problems in Artificial Intelligence and formal verification. Accordingly, it is well suited for (junior and senior) undergraduate and graduate students majoring in Computer Science or mathematics. Each chapter has about a dozen or so exercises to help the reader understand the materials.

Название: Ensemble Methods: Foundations and Algorithms, 2nd Edition
Автор: Zhi-Hua Zhou
Издательство: CRC Press
Серия: Chapman & Hall/CRC Machine Learning & Pattern Recognition
Год: 2025
Страниц: 364
Язык: английский
Формат: pdf (true), epub
Размер: 28.5 MB

Ensemble methods that train multiple learners and then combine them to use, with Boosting and Bagging as representatives, are well-known Machine Learning approaches. It has become common sense that an ensemble is usually significantly more accurate than a single learner, and ensemble methods have already achieved great success in various real-world tasks. Twelve years have passed since the publication of the first edition of the book in 2012. Many significant advances in this field have been developed. First, many theoretical issues have been tackled, for example, the fundamental question of why AdaBoost seems resistant to overfitting gets addressed, so that now we understand much more about the essence of ensemble methods. Second, ensemble methods have been well developed in more Machine Learning fields, e.g., isolation forest in anomaly detection, so that now we have powerful ensemble methods for tasks beyond conventional supervised learning. Third, ensemble mechanisms have also been found helpful in emerging areas such as Deep Learning and online learning.

Название: Coding mit KI für Dummies / Программирование с ИИ для чайников
Автор: Chris Minnick
Издательство: Wiley-VCH GmbH
Год: 2025
Страниц: 422
Язык: немецкий
Формат: epub (true)
Размер: 53,5 MB

Von der Prozessautomatisierung über die Code-Optimierung bis hin zur Erledigung von Kernaufgaben wie Dokumentation, Debugging und Aktualisierung - künstliche Intelligenz hilft Ihnen dabei, sich auf den Kern Ihrer Entwicklungsarbeit zu konzentrieren. In diesem Buch lernen Sie die wichtigsten Plattformen kennen, die Sie beim Coding unterstützen können. Sie erfahren, welche Möglichkeiten und welche Grenzen die KI-Tools haben und wie Sie diese für Routineaufgaben einsetzen, um neuen Code zu schreiben und Ihre Codequalität zu verbessern. So behalten Sie den Kopf frei für die wichtigen Aufgaben.

Название: Encyclopedia of Cryptography, Security and Privacy, 3rd Edition
Автор: Sushil Jajodia, Pierangela Samarati, Moti Yung
Издательство: Springer
Год: 2025
Страниц: 2864
Язык: английский
Формат: pdf (true)
Размер: 65.7 MB

A rich stream of papers and many good books have been written on cryptography, security, and privacy, but most of them assume a scholarly reader who has the time to start at the beginning and work his way through the entire text. The goal of Encyclopedia of Cryptography, Security, and Privacy, Third Edition is to make important notions of cryptography, security, and privacy accessible to readers who have an interest in a particular concept related to these areas, but who lack the time to study one of the many books in these areas. Cryptography is the discipline of writing a message in ciphertext (Cryptosystem), usually by a translation from plaintext according to some (frequently changing) keytext, with the aim of protecting a secret from adversaries, interceptors, intruders, interlopers, eavesdroppers, opponents or simply attackers, opponents, and enemies. Professional cryptography protects not only the plaintext, but also the key and more generally tries to protect the whole cryptosystem.

Название: Алгоритмы и модели вычисления
Автор: Голубенко Д., Крошин А., Горбунов Э.
Издательство: МФТИ
Год: 2019
Cтраниц: 240
Формат: pdf (ocr)
Размер: 32 мб
Язык: русский

Многие школьники изучают алгоритмы, готовясь к олимпиадам по программированию. Возможно, что эта книга поможет математикам-олимпиадникам, не занимавшимся алгоритмами, заинтересоваться олимпиадным программированием, а может быть - и теорией алгоритмов.

Название: Программирование в Clojure: Практика применения Lisp в мире Java
Автор: Эмерик Ч., Карпер Б., Гранд К.
Издательство: Москва
Год: 2013
Cтраниц: 815
Формат: pdf
Размер: 34 мб
Язык: русский

Почему многие выбирают Clojure? Это - функциональный язык программирования, не только позволяющий пользоваться Java-библиотеками, службами и другими ресурсами JVM, но и соперничающий с другими динамическими языками, такими как Ruby и Python. В этом исчерпывающем руководстве вы познакомитесь с основами программирования на Clojure на примерах решения повседневных задач, которые могут быть знакомы вам по другим, известным языкам программирования.

Название: Clean Code With Java: Best practices 101
Автор: Aarav Joshi
Издательство: 101 Books
Год: December 18, 2024
Страниц: 379
Язык: английский
Формат: pdf
Размер: 29.1 MB

Clean code is the cornerstone of professional software development. It ensures that programs are not only functional but also maintainable, scalable, and easy to understand. Writing clean code goes beyond aesthetics; it’s about crafting solutions that can adapt to evolving requirements, empower collaboration, and minimize technical debt. Clean code leads to better performance, fewer bugs, and happier developers. Java, being one of the most widely used programming languages, is a prime candidate for clean coding techniques. Its robust object-oriented features and extensive ecosystem make it powerful but also susceptible to complexity. Clean coding in Java emphasizes principles like meaningful naming, single responsibility, proper encapsulation, and effective error handling, which together foster robust and scalable applications. This book is a comprehensive guide to writing clean, maintainable Java code. Drawing inspiration from best-selling works, it blends theory, real-world examples, and actionable tips, empowering developers to master the art of clean coding.

Название: Information Architecture and UX Design: The Integration of Information Spaces, Third Edition
Автор: Wei Ding, Xia Lin, Michael Zarro
Издательство: Springer
Год: 2025
Страниц: 175
Язык: английский
Формат: pdf (true), epub
Размер: 15.7 MB

This book explores integrated information spaces in the web context and beyond, with a focus on putting theories and principles into practice. The authors illustrate the heightened significance of Information Architecture (IA) and User Experience (UX) in industry and society. Building on foundational perspectives, the book explores advanced topics such as user research, the evolving role of Artificial Intelligence (AI), human information behaviors, and systems thinking. This Third Edition adopts a forward-looking approach to integrated web, social media, business tools, and more. Additionally, the book covers advancements in information technologies since the last release, including Generative AI and evolving IA/UX practices.

Название: Building Generative AI Services with FastAPI: A Practical Approach to Developing Context Rich Generative AI Applications (5th Early Release)
Автор: Ali Parandeh
Издательство: O’Reilly Media, Inc.
Год: 2024-12-04
Страниц: 398
Язык: английский
Формат: epub
Размер: 23.0 MB

Ready to build applications using Generative AI? This practical book outlines the process necessary to design and build production grade AI services with a FastAPI web server that communicate seamlessly with databases, payment systems, and external APIs. You'll learn how to develop autonomous generative AI agents that stream outputs in real-time and interact with other models. Web developers, data scientists, and DevOps engineers will learn to implement end-to-end production-ready services that leverage Generative AI. You'll learn design patterns to manage software complexity, implement FastAPI lifespan for AI model integration, handle long-running generative tasks, perform content filtering, cache outputs, implement retrieval augmented generation (RAG) with a vector database, implement usage/cost monitoring and tracking, protect services with your own authentication and authorization mechanisms, and effectively control stream outputs directly from GenAI models.

Название: Introduction to Biometrics, 2nd Edition
Автор: Anil K. Jain, Arun A. Ross, Karthik Nandakumar, Thomas Swearingen
Издательство: Springer
Серия: Texts in Computer Science
Год: 2025
Страниц: 418
Язык: английский
Формат: pdf (true)
Размер: 33.2 MB

This textbook introduces the fundamental concepts and techniques used in biometric recognition to students, practitioners, and non-experts in the field. Specifically, the book describes key methodologies used for sensing, feature extraction, and matching of commonly used biometric modalities such as fingerprint, face, iris, and voice. In addition, it presents techniques for fusion of biometric information to meet stringent accuracy requirements, also discussing various security issues and associated remedies involved in the deployment of biometric systems. Biometric recognition, or simply biometrics, is the science and technology of establishing the identity of a person based on physical or behavioral attributes such as fingerprint, face, iris, and voice. By capturing these attributes using appropriately designed sensors, representing them in a digital format, and comparing this recorded data against the data acquired from the same person at an earlier time instance (enrollment), it is possible to automate the process of person recognition in real time. Thus, biometric recognition can be viewed as a Machine Learning problem, where the machine learns the salient features (patterns) in the biometric attributes of an individual and robustly matches such patterns efficiently and effectively with enrollment patterns.